Performance Improvement of Inertial Navigation System by Using Magnetometer with Vehicle Dynamic Constraints

Abstract

A navigation algorithm is proposed to increase the inertial navigation performance of a ground vehicle using magnetic measurements and dynamic constraints. The navigation solutions are estimated based on inertial measurements such as acceleration and angular velocity measurements. To improve the inertial navigation performance, a three-axis magnetometer is used to provide the heading angle, and nonholonomic constraints (NHCs) are introduced to increase the correlation between the velocity and the attitude equation. The NHCs provide a velocity feedback to the attitude, which makes the navigation solution more robust. Additionally, an acceleration-based roll and pitch estimation is applied to decrease the drift when the acceleration is within certain boundaries. The magnetometer and NHCs are combined with an extended Kalman filter. An experimental test was conducted to verify the proposed method, and a comprehensive analysis of the performance in terms of the position, velocity, and attitude showed that the navigation performance could be improved by using the magnetometer and NHCs. Moreover, the proposed method could improve the estimation performance for the position, velocity, and attitude without any additional hardware except an inertial sensor and magnetometer. Therefore, this method would be effective for ground vehicles, indoor navigation, mobile robots, vehicle navigation in urban canyons, or navigation in any global navigation satellite system-denied environment.

1-Point RANSAC UKF with Inverse Covariance Intersection for Fault Tolerance

“…P D,DR is the height obtained from the pure navigation output. φ acc and θ acc are also the roll and pitch angle calculated by the accelerometer [35,36]. ψ is the yaw angle, and θ is the pitch angle of the target system [33].…”

“…In addition, the true value of the altitude was determined by the values obtained from the terrain information database and the integrated navigation system (Trimble DR + GPS, performance characteristic of the system: less than 3 m altitude error).  are also the roll and pitch angle calculated by the accelerometer [35,36].  is the yaw angle, and  is the pitch angle of the target system [33].…”

Ultrasonic Based Heading Estimation for Aiding Land Vehicle Navigation in GNSS Denied Environment

“…Therefore, GNSS/INS integration navigation system should be aided with other sensors to mitigate the large drift of the INS during GNSS signal outage (Niu et al, 2007). Many previous researches used various aiding sensors such as LiDAR (Gao et al, 2015), cameras (Lee et al, 2015), RADAR (Abosekeen et al, 2018), magnetometer (Won et al, 2015), and odometers. There are some disadvantages when using the previously mentioned sensors to aid INS such as some of them are expensive as the case of LiDAR and RADAR, others need very high computational and processing capability as in the case of LiDAR and cameras, others are affected by the surrounding environment as in the case of magnetic interference for the magnetometers and the weather and lighting conditions as the case of cameras and finally odometer may provide inaccurate information to the navigation system in some situations such as land vehicle slipping condition (Wang et al, 2015), or when there is some issues related to the wheels such as the wheels misalignment and unequal wheel diameters (Borenstein, 1996).…”

MEMS 3D DR/GPS Integrated System for Land Vehicle Application Robust to GPS Outages

“…To solve this problem, additional sensors such as odometer and magnetometer are used to correct the navigation errors. Previous works [4], [11] combined odometer to correct velocity error and barometer to correct altitude error, but the performance of the corrected system was not sufficient for 3D applications.…”

“…However, RTS smoother is not appropriate in real-time applications since it requires postprocessing. Similarly, NHC and magnetometers were used to increase heading accuracy [11]. NHC is the kinematic constraint of a land vehicle that assumes the speed perpendicular to the forward direction of the vehicle is zero.…”